Data Engineering should be an extension of Software Engineering (SE), which can be defined as the "establishment and use of sound engineering principles to obtain economically software that is reliable and works on real machines efficiently" (Friedrich Bauer, 1972). If you consider this, then a lot of what you said is covered by SE.

This was a long post, though is not a negative aspect. Probably each section would have deserved own post. The sections on metrics or zero-trust security principle don’t seem to belong in the article.

Many practices described are not basic. Basic for me means “what do I need to do my job”, though it doesn’t necessarily mean that what I do is efficient. A good architect is efficient and addresses other organizational needs, while mastery involves going beyond one’s job and finding new way to improve the quality of one’s work. Does it make sense?

Data Engineering is about data architecture but not limited to it.